Finding Naval Ship Maintenance Expertise Through Text Mining and SNA (텍스트마이닝 및 SNA을 통한 해군 함정정비 전문가 탐색)

Jin-Gwang Kim (김진광); SoungWoong Yoon (윤성웅); Lee Sang Hoon (이상훈)

doi:10.9708/jksci.2019.24.07.125

Finding Naval Ship Maintenance Expertise Through Text Mining and SNA

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2019, 24(7), pp.125-133
DOI : 10.9708/jksci.2019.24.07.125
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : April 30, 2019
Accepted : June 26, 2019
Published : July 31, 2019

Jin-Gwang Kim ¹, SoungWoong Yoon ¹, Lee Sang Hoon ¹

¹국방대학교

Accredited

ABSTRACT

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

KEYWORDS

Collaboration relationship, Expert, Social Network Analysis(SNA), Text Mining

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* References for papers published after 2023 are currently being built.

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[journal] 임상수 / 2019 / A study on military organizational tasks analysis methodology / 한국데이터정보과학회지 / 한국데이터정보과학회 30(1) : 139~157

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[thesis] Zafarani / 2014 / Social Media Mining / Cambridge Univ

KJCKorea
Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Finding Naval Ship Maintenance Expertise Through Text Mining and SNA

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Finding Naval Ship Maintenance Expertise Through Text Mining and SNA

ABSTRACT

KEYWORDS

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REFERENCES (10) * References for papers published after 2023 are currently being built.

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* References for papers published after 2023 are currently being built.